Work

scMRdb: a comprehensive resource for cell-type-resolved Mendelian randomization of complex traits

Year: 2026

Type: article

Abstract: Mendelian randomization (MR) is a powerful analytical approach to infer putative causal links between gene expression and human disease, using genetic variants as instrumental variables to mitigate confounding and reverse causation. However, existing MR resources predominantly rely on bulk-tissue expression quantitative trait loci (eQTLs), which mask cell-type-specific transcriptional effects by averaging expression across cellular populations. Furthermore, cell-type-resolved causal evidence from single-cell eQTL (sc-eQTL) MR analyses remains fragmented across individual studies with inconsistent workflows, prohibiting standardized cross-cell-type comparisons. Here we present scMRdb (https://ngdc.cncb.ac.cn/scmrdb), a comprehensive resource for cell-type-resolved MR of human complex traits and diseases. scMRdb harmonizes 5206 genome-wide association study (GWAS) summary statistics of European and East Asian ancestry with 585 sc-eQTL datasets spanning 11 tissues and cell systems, including 110 cell types. A uniform pipeline evaluates all gene-trait pairs via MR followed by Steiger directionality testing. Significant associations are assessed by colocalization, and results are stratified into six confidence tiers with integrated drug-target annotation. scMRdb enables systematic recovery of candidate causal genes supported by cell-type-resolved regulatory evidence that is often diluted or obscured in bulk-tissue analyses. We expect scMRdb to serve as a user-friendly portal for generating cell-type-informed mechanistic hypotheses and prioritizing actionable therapeutic targets for complex human diseases.

Source: Nucleic Acids Research

DOI: 10.1093/nar/gkag1063

Authors: Siyu Pan, Ziyang Wang, Peilin Jia

Institutions: Chinese Academy of Sciences, Beijing Institute of Genomics, University of Chinese Academy of Sciences

Language: English

Topic: Genetic Associations and Epidemiology

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,992